Computer modelling of statistical, structural and neural network methods of pattern recognition

Pattern recognition is one of the most important tasks of both intelligent control systems and artificial intelligence. The paper substantiates the relevance of the study of computer modelling of statistical, structural and neural network methods of pattern recognition. The article presents a comparative analysis of the quality of pattern recognition using the Hamming neural network and the statistical algorithm. The analysis shows that the use of the Hamming neural network is preferable in most cases. Computer modelling of the structural method using the Freeman code gives a description that allows us to unambiguously assign an object to its class. Based on the analysis of the results of computer modelling, the positive and negative aspects of each method are revealed. As a result, the structural method is the most optimal.